code: def test_predict_feature_columns():
      preprocessor = DummyPreprocessor()
      predictor = LightGBMPredictor(
          model=model, preprocessor=preprocessor
      )
  
      data_batch = np.array([[1, 2, 7], [3, 4, 8], [5, 6, 9]])
      predictions = predictor.predict(
          data_batch, feature_columns=[0, 1]
      )
  
      assert len(predictions) == 3
      assert predictor.get_preprocessor().has_preprocessed
  
file_path: ray/python/ray/train/tests/test_lightgbm_predictor.py
imports: import re
  import lightgbm
  import numpy
  import pandas
  import pytest
  from ray.air.constants import MAX_REPR_LENGTH
  from ray.air.util.data_batch_conversion import _convert_pandas_to_batch_type
  from ray.train.lightgbm import LightGBMCheckpoint, LightGBMPredictor
  from ray.train.predictor import TYPE_TO_ENUM
  from ray.train.tests.dummy_preprocessor import DummyPreprocessor
label_desc: Use image node_id 5 for calling a global function with example usage: test_predict_feature_columns() without return types